blob: 919968e611ddd2abee4cb608fc4281886cb954b7 [file] [log] [blame]
import controls
import numpy
import os
class Constant(object):
def __init__(self, name, formatt, value):
self.name = name
self.formatt = formatt
self.value = value
self.formatToType = {}
self.formatToType['%f'] = "double"
self.formatToType['%d'] = "int"
def Render(self, loop_type):
typestring = self.formatToType[self.formatt]
if loop_type == 'float' and typestring == 'double':
typestring = loop_type
return str("\nstatic constexpr %s %s = "+ self.formatt +";\n") % \
(typestring, self.name, self.value)
class ControlLoopWriter(object):
def __init__(self,
gain_schedule_name,
loops,
namespaces=None,
write_constants=False,
plant_type='StateFeedbackPlant',
observer_type='StateFeedbackObserver',
scalar_type='double'):
"""Constructs a control loop writer.
Args:
gain_schedule_name: string, Name of the overall controller.
loops: array[ControlLoop], a list of control loops to gain schedule
in order.
namespaces: array[string], a list of names of namespaces to nest in
order. If None, the default will be used.
plant_type: string, The C++ type of the plant.
observer_type: string, The C++ type of the observer.
scalar_type: string, The C++ type of the base scalar.
"""
self._gain_schedule_name = gain_schedule_name
self._loops = loops
if namespaces:
self._namespaces = namespaces
else:
self._namespaces = ['frc971', 'control_loops']
self._namespace_start = '\n'.join(
['namespace %s {' % name for name in self._namespaces])
self._namespace_end = '\n'.join([
'} // namespace %s' % name for name in reversed(self._namespaces)
])
self._constant_list = []
self._plant_type = plant_type
self._observer_type = observer_type
self._scalar_type = scalar_type
def AddConstant(self, constant):
"""Adds a constant to write.
Args:
constant: Constant, the constant to add to the header.
"""
self._constant_list.append(constant)
def _TopDirectory(self):
return self._namespaces[0]
def _HeaderGuard(self, header_file):
return ('_'.join([namespace.upper() for namespace in self._namespaces])
+ '_' + os.path.basename(header_file).upper().replace(
'.', '_').replace('/', '_') + '_')
def Write(self, header_file, cc_file):
"""Writes the loops to the specified files."""
self.WriteHeader(header_file)
self.WriteCC(os.path.basename(header_file), cc_file)
def _GenericType(self, typename, extra_args=None):
"""Returns a loop template using typename for the type."""
num_states = self._loops[0].A.shape[0]
num_inputs = self._loops[0].B.shape[1]
num_outputs = self._loops[0].C.shape[0]
if extra_args is not None:
extra_args = ', ' + extra_args
else:
extra_args = ''
if self._scalar_type != 'double':
extra_args += ', ' + self._scalar_type
return '%s<%d, %d, %d%s>' % (typename, num_states, num_inputs,
num_outputs, extra_args)
def _ControllerType(self):
"""Returns a template name for StateFeedbackController."""
return self._GenericType('StateFeedbackController')
def _ObserverType(self):
"""Returns a template name for StateFeedbackObserver."""
return self._GenericType(self._observer_type)
def _LoopType(self):
"""Returns a template name for StateFeedbackLoop."""
num_states = self._loops[0].A.shape[0]
num_inputs = self._loops[0].B.shape[1]
num_outputs = self._loops[0].C.shape[0]
return 'StateFeedbackLoop<%d, %d, %d, %s, %s, %s>' % (
num_states, num_inputs, num_outputs, self._scalar_type,
self._PlantType(), self._ObserverType())
def _PlantType(self):
"""Returns a template name for StateFeedbackPlant."""
return self._GenericType(self._plant_type)
def _PlantCoeffType(self):
"""Returns a template name for StateFeedbackPlantCoefficients."""
return self._GenericType(self._plant_type + 'Coefficients')
def _ControllerCoeffType(self):
"""Returns a template name for StateFeedbackControllerCoefficients."""
return self._GenericType('StateFeedbackControllerCoefficients')
def _ObserverCoeffType(self):
"""Returns a template name for StateFeedbackObserverCoefficients."""
return self._GenericType(self._observer_type + 'Coefficients')
def WriteHeader(self, header_file):
"""Writes the header file to the file named header_file."""
with open(header_file, 'w') as fd:
header_guard = self._HeaderGuard(header_file)
fd.write('#ifndef %s\n'
'#define %s\n\n' % (header_guard, header_guard))
fd.write(
'#include \"frc971/control_loops/state_feedback_loop.h\"\n')
if (self._plant_type == 'StateFeedbackHybridPlant' or
self._observer_type == 'HybridKalman'):
fd.write(
'#include \"frc971/control_loops/hybrid_state_feedback_loop.h\"\n'
)
fd.write('\n')
fd.write(self._namespace_start)
for const in self._constant_list:
fd.write(const.Render(self._scalar_type))
fd.write('\n\n')
for loop in self._loops:
fd.write(loop.DumpPlantHeader(self._PlantCoeffType()))
fd.write('\n')
fd.write(loop.DumpControllerHeader(self._scalar_type))
fd.write('\n')
fd.write(loop.DumpObserverHeader(self._ObserverCoeffType()))
fd.write('\n')
fd.write('%s Make%sPlant();\n\n' % (self._PlantType(),
self._gain_schedule_name))
fd.write('%s Make%sController();\n\n' % (self._ControllerType(),
self._gain_schedule_name))
fd.write('%s Make%sObserver();\n\n' % (self._ObserverType(),
self._gain_schedule_name))
fd.write('%s Make%sLoop();\n\n' % (self._LoopType(),
self._gain_schedule_name))
fd.write(self._namespace_end)
fd.write('\n\n')
fd.write("#endif // %s\n" % header_guard)
def WriteCC(self, header_file_name, cc_file):
"""Writes the cc file to the file named cc_file."""
with open(cc_file, 'w') as fd:
fd.write('#include \"%s/%s\"\n' % (os.path.join(*self._namespaces),
header_file_name))
fd.write('\n')
fd.write('#include <vector>\n')
fd.write('\n')
fd.write(
'#include \"frc971/control_loops/state_feedback_loop.h\"\n')
fd.write('\n')
fd.write(self._namespace_start)
fd.write('\n\n')
for loop in self._loops:
fd.write(
loop.DumpPlant(self._PlantCoeffType(), self._scalar_type))
fd.write('\n')
for loop in self._loops:
fd.write(loop.DumpController(self._scalar_type))
fd.write('\n')
for loop in self._loops:
fd.write(
loop.DumpObserver(self._ObserverCoeffType(),
self._scalar_type))
fd.write('\n')
fd.write('%s Make%sPlant() {\n' % (self._PlantType(),
self._gain_schedule_name))
fd.write(' ::std::vector< ::std::unique_ptr<%s>> plants(%d);\n' %
(self._PlantCoeffType(), len(self._loops)))
for index, loop in enumerate(self._loops):
fd.write(' plants[%d] = ::std::unique_ptr<%s>(new %s(%s));\n' %
(index, self._PlantCoeffType(), self._PlantCoeffType(),
loop.PlantFunction()))
fd.write(' return %s(&plants);\n' % self._PlantType())
fd.write('}\n\n')
fd.write('%s Make%sController() {\n' % (self._ControllerType(),
self._gain_schedule_name))
fd.write(
' ::std::vector< ::std::unique_ptr<%s>> controllers(%d);\n' %
(self._ControllerCoeffType(), len(self._loops)))
for index, loop in enumerate(self._loops):
fd.write(
' controllers[%d] = ::std::unique_ptr<%s>(new %s(%s));\n' %
(index, self._ControllerCoeffType(),
self._ControllerCoeffType(), loop.ControllerFunction()))
fd.write(' return %s(&controllers);\n' % self._ControllerType())
fd.write('}\n\n')
fd.write('%s Make%sObserver() {\n' % (self._ObserverType(),
self._gain_schedule_name))
fd.write(' ::std::vector< ::std::unique_ptr<%s>> observers(%d);\n'
% (self._ObserverCoeffType(), len(self._loops)))
for index, loop in enumerate(self._loops):
fd.write(
' observers[%d] = ::std::unique_ptr<%s>(new %s(%s));\n'
% (index, self._ObserverCoeffType(),
self._ObserverCoeffType(), loop.ObserverFunction()))
fd.write(' return %s(&observers);\n' % self._ObserverType())
fd.write('}\n\n')
fd.write('%s Make%sLoop() {\n' % (self._LoopType(),
self._gain_schedule_name))
fd.write(
' return %s(Make%sPlant(), Make%sController(), Make%sObserver());\n'
% (self._LoopType(), self._gain_schedule_name,
self._gain_schedule_name, self._gain_schedule_name))
fd.write('}\n\n')
fd.write(self._namespace_end)
fd.write('\n')
class ControlLoop(object):
def __init__(self, name):
"""Constructs a control loop object.
Args:
name: string, The name of the loop to use when writing the C++ files.
"""
self._name = name
@property
def name(self):
"""Returns the name"""
return self._name
def ContinuousToDiscrete(self, A_continuous, B_continuous, dt):
"""Calculates the discrete time values for A and B.
Args:
A_continuous: numpy.matrix, The continuous time A matrix
B_continuous: numpy.matrix, The continuous time B matrix
dt: float, The time step of the control loop
Returns:
(A, B), numpy.matrix, the control matricies.
"""
return controls.c2d(A_continuous, B_continuous, dt)
def InitializeState(self):
"""Sets X, Y, and X_hat to zero defaults."""
self.X = numpy.zeros((self.A.shape[0], 1))
self.Y = self.C * self.X
self.X_hat = numpy.zeros((self.A.shape[0], 1))
def PlaceControllerPoles(self, poles):
"""Places the controller poles.
Args:
poles: array, An array of poles. Must be complex conjegates if they have
any imaginary portions.
"""
self.K = controls.dplace(self.A, self.B, poles)
def PlaceObserverPoles(self, poles):
"""Places the observer poles.
Args:
poles: array, An array of poles. Must be complex conjegates if they have
any imaginary portions.
"""
self.L = controls.dplace(self.A.T, self.C.T, poles).T
def Update(self, U):
"""Simulates one time step with the provided U."""
#U = numpy.clip(U, self.U_min, self.U_max)
self.X = self.A * self.X + self.B * U
self.Y = self.C * self.X + self.D * U
def PredictObserver(self, U):
"""Runs the predict step of the observer update."""
self.X_hat = (self.A * self.X_hat + self.B * U)
def CorrectObserver(self, U):
"""Runs the correct step of the observer update."""
if hasattr(self, 'KalmanGain'):
KalmanGain = self.KalmanGain
else:
KalmanGain = numpy.linalg.inv(self.A) * self.L
self.X_hat += KalmanGain * (self.Y - self.C * self.X_hat - self.D * U)
def UpdateObserver(self, U):
"""Updates the observer given the provided U."""
if hasattr(self, 'KalmanGain'):
KalmanGain = self.KalmanGain
else:
KalmanGain = numpy.linalg.inv(self.A) * self.L
self.X_hat = (self.A * self.X_hat + self.B * U + self.A * KalmanGain *
(self.Y - self.C * self.X_hat - self.D * U))
def _DumpMatrix(self, matrix_name, matrix, scalar_type):
"""Dumps the provided matrix into a variable called matrix_name.
Args:
matrix_name: string, The variable name to save the matrix to.
matrix: The matrix to dump.
scalar_type: The C++ type to use for the scalar in the matrix.
Returns:
string, The C++ commands required to populate a variable named matrix_name
with the contents of matrix.
"""
ans = [
' Eigen::Matrix<%s, %d, %d> %s;\n' % (scalar_type, matrix.shape[0],
matrix.shape[1], matrix_name)
]
for x in xrange(matrix.shape[0]):
for y in xrange(matrix.shape[1]):
write_type = repr(matrix[x, y])
if scalar_type == 'float':
if '.' not in write_type:
write_type += '.0'
write_type += 'f'
ans.append(
' %s(%d, %d) = %s;\n' % (matrix_name, x, y, write_type))
return ''.join(ans)
def DumpPlantHeader(self, plant_coefficient_type):
"""Writes out a c++ header declaration which will create a Plant object.
Returns:
string, The header declaration for the function.
"""
return '%s Make%sPlantCoefficients();\n' % (plant_coefficient_type,
self._name)
def DumpPlant(self, plant_coefficient_type, scalar_type):
"""Writes out a c++ function which will create a PlantCoefficients object.
Returns:
string, The function which will create the object.
"""
ans = [
'%s Make%sPlantCoefficients() {\n' % (plant_coefficient_type,
self._name)
]
ans.append(self._DumpMatrix('C', self.C, scalar_type))
ans.append(self._DumpMatrix('D', self.D, scalar_type))
ans.append(self._DumpMatrix('U_max', self.U_max, scalar_type))
ans.append(self._DumpMatrix('U_min', self.U_min, scalar_type))
if plant_coefficient_type.startswith('StateFeedbackPlant'):
ans.append(self._DumpMatrix('A', self.A, scalar_type))
ans.append(self._DumpMatrix('B', self.B, scalar_type))
ans.append(
' return %s'
'(A, B, C, D, U_max, U_min);\n' % (plant_coefficient_type))
elif plant_coefficient_type.startswith('StateFeedbackHybridPlant'):
ans.append(
self._DumpMatrix('A_continuous', self.A_continuous,
scalar_type))
ans.append(
self._DumpMatrix('B_continuous', self.B_continuous,
scalar_type))
ans.append(' return %s'
'(A_continuous, B_continuous, C, D, U_max, U_min);\n' %
(plant_coefficient_type))
else:
glog.fatal('Unsupported plant type %s', plant_coefficient_type)
ans.append('}\n')
return ''.join(ans)
def PlantFunction(self):
"""Returns the name of the plant coefficient function."""
return 'Make%sPlantCoefficients()' % self._name
def ControllerFunction(self):
"""Returns the name of the controller function."""
return 'Make%sControllerCoefficients()' % self._name
def ObserverFunction(self):
"""Returns the name of the controller function."""
return 'Make%sObserverCoefficients()' % self._name
def DumpControllerHeader(self, scalar_type):
"""Writes out a c++ header declaration which will create a Controller object.
Returns:
string, The header declaration for the function.
"""
num_states = self.A.shape[0]
num_inputs = self.B.shape[1]
num_outputs = self.C.shape[0]
return 'StateFeedbackControllerCoefficients<%d, %d, %d, %s> %s;\n' % (
num_states, num_inputs, num_outputs, scalar_type,
self.ControllerFunction())
def DumpController(self, scalar_type):
"""Returns a c++ function which will create a Controller object.
Returns:
string, The function which will create the object.
"""
num_states = self.A.shape[0]
num_inputs = self.B.shape[1]
num_outputs = self.C.shape[0]
ans = [
'StateFeedbackControllerCoefficients<%d, %d, %d, %s> %s {\n' %
(num_states, num_inputs, num_outputs, scalar_type,
self.ControllerFunction())
]
ans.append(self._DumpMatrix('K', self.K, scalar_type))
if not hasattr(self, 'Kff'):
self.Kff = numpy.matrix(numpy.zeros(self.K.shape))
ans.append(self._DumpMatrix('Kff', self.Kff, scalar_type))
ans.append(
' return StateFeedbackControllerCoefficients<%d, %d, %d, %s>'
'(K, Kff);\n' % (num_states, num_inputs, num_outputs, scalar_type))
ans.append('}\n')
return ''.join(ans)
def DumpObserverHeader(self, observer_coefficient_type):
"""Writes out a c++ header declaration which will create a Observer object.
Returns:
string, The header declaration for the function.
"""
return '%s %s;\n' % (observer_coefficient_type, self.ObserverFunction())
def DumpObserver(self, observer_coefficient_type, scalar_type):
"""Returns a c++ function which will create a Observer object.
Returns:
string, The function which will create the object.
"""
ans = [
'%s %s {\n' % (observer_coefficient_type, self.ObserverFunction())
]
if observer_coefficient_type.startswith('StateFeedbackObserver'):
if hasattr(self, 'KalmanGain'):
KalmanGain = self.KalmanGain
Q = self.Q
R = self.R
else:
KalmanGain = numpy.linalg.inv(self.A) * self.L
Q = numpy.zeros(self.A.shape)
R = numpy.zeros((self.C.shape[0], self.C.shape[0]))
ans.append(self._DumpMatrix('KalmanGain', KalmanGain, scalar_type))
ans.append(self._DumpMatrix('Q', Q, scalar_type))
ans.append(self._DumpMatrix('R', R, scalar_type))
ans.append(' return %s(KalmanGain, Q, R);\n' %
(observer_coefficient_type,))
elif observer_coefficient_type.startswith('HybridKalman'):
ans.append(
self._DumpMatrix('Q_continuous', self.Q_continuous,
scalar_type))
ans.append(
self._DumpMatrix('R_continuous', self.R_continuous,
scalar_type))
ans.append(
self._DumpMatrix('P_steady_state', self.P_steady_state,
scalar_type))
ans.append(
' return %s(Q_continuous, R_continuous, P_steady_state);\n' %
(observer_coefficient_type,))
else:
glog.fatal('Unsupported observer type %s',
observer_coefficient_type)
ans.append('}\n')
return ''.join(ans)
class HybridControlLoop(ControlLoop):
def __init__(self, name):
super(HybridControlLoop, self).__init__(name=name)
def Discretize(self, dt):
[self.A, self.B, self.Q, self.R] = \
controls.kalmd(self.A_continuous, self.B_continuous,
self.Q_continuous, self.R_continuous, dt)
def PredictHybridObserver(self, U, dt):
self.Discretize(dt)
self.X_hat = self.A * self.X_hat + self.B * U
self.P = (self.A * self.P * self.A.T + self.Q)
def CorrectHybridObserver(self, U):
Y_bar = self.Y - self.C * self.X_hat
C_t = self.C.T
S = self.C * self.P * C_t + self.R
self.KalmanGain = self.P * C_t * numpy.linalg.inv(S)
self.X_hat = self.X_hat + self.KalmanGain * Y_bar
self.P = (numpy.eye(len(self.A)) - self.KalmanGain * self.C) * self.P
def InitializeState(self):
super(HybridControlLoop, self).InitializeState()
if hasattr(self, 'Q_steady_state'):
self.P = self.Q_steady_state
else:
self.P = numpy.matrix(
numpy.zeros((self.A.shape[0], self.A.shape[0])))
class CIM(object):
def __init__(self):
# Stall Torque in N m
self.stall_torque = 2.42
# Stall Current in Amps
self.stall_current = 133.0
# Free Speed in rad/s
self.free_speed = 5500.0 / 60.0 * 2.0 * numpy.pi
# Free Current in Amps
self.free_current = 4.7
# Resistance of the motor
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = (
self.free_speed / (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
class MiniCIM(object):
def __init__(self):
# Stall Torque in N m
self.stall_torque = 1.41
# Stall Current in Amps
self.stall_current = 89.0
# Free Speed in rad/s
self.free_speed = 5840.0 / 60.0 * 2.0 * numpy.pi
# Free Current in Amps
self.free_current = 3.0
# Resistance of the motor
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = (
self.free_speed / (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
class NMotor(object):
def __init__(self, motor, n):
"""Gangs together n motors."""
self.motor = motor
self.stall_torque = motor.stall_torque * n
self.stall_current = motor.stall_current * n
self.free_speed = motor.free_speed
self.free_current = motor.free_current * n
self.resistance = motor.resistance / n
self.Kv = motor.Kv
self.Kt = motor.Kt
self.motor_inertia = motor.motor_inertia * n
class Vex775Pro(object):
def __init__(self):
# Stall Torque in N m
self.stall_torque = 0.71
# Stall Current in Amps
self.stall_current = 134.0
# Free Speed in rad/s
self.free_speed = 18730.0 / 60.0 * 2.0 * numpy.pi
# Free Current in Amps
self.free_current = 0.7
# Resistance of the motor
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = (
self.free_speed / (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
# Motor inertia in kg m^2
self.motor_inertia = 0.00001187
class BAG(object):
# BAG motor specs available at http://motors.vex.com/vexpro-motors/bag-motor
def __init__(self):
# Stall Torque in (N m)
self.stall_torque = 0.43
# Stall Current in (Amps)
self.stall_current = 53.0
# Free Speed in (rad/s)
self.free_speed = 13180.0 / 60.0 * 2.0 * numpy.pi
# Free Current in (Amps)
self.free_current = 1.8
# Resistance of the motor (Ohms)
self.resistance = 12.0 / self.stall_current
# Motor velocity constant (radians / (sec * volt))
self.Kv = (
self.free_speed / (12.0 - self.resistance * self.free_current))
# Torque constant (N * m / A)
self.Kt = self.stall_torque / self.stall_current
# Motor inertia in kg m^2
self.motor_inertia = 0.000006
class MN3510(object):
def __init__(self):
# http://www.robotshop.com/en/t-motor-navigator-mn3510-360kv-brushless-motor.html#Specifications
# Free Current in Amps
self.free_current = 0.0
# Resistance of the motor
self.resistance = 0.188
# Stall Current in Amps
self.stall_current = 14.0 / self.resistance
# Motor velocity constant
self.Kv = 360.0 / 60.0 * (2.0 * numpy.pi)
# Torque constant Nm / A
self.Kt = 1.0 / self.Kv
# Stall Torque in N m
self.stall_torque = self.Kt * self.stall_current
class Falcon(object):
"""Class representing the VexPro Falcon 500 motor.
All numbers based on data from
https://www.vexrobotics.com/vexpro/falcon-500."""
def __init__(self):
# Stall Torque in N m
self.stall_torque = 4.69
# Stall Current in Amps
self.stall_current = 257.0
# Free Speed in rad / sec
self.free_speed = 6380.0 / 60.0 * 2.0 * numpy.pi
# Free Current in Amps
self.free_current = 1.5
# Resistance of the motor, divided by 2 to account for the 2 motors
self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = (self.free_speed /
(12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current